Building Rapport through Dynamic Models of Acoustic-Prosodic Entrainment

Lubold, Nichola

doi:10.1145/3027063.3027132

Cited by 4 publications

(8 citation statements)

References 6 publications

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“…In our analyses here, we did observe that children's LSM scores correlated positively with their emulation of the robot during storytelling, as expected (H2). This suggests that rapport is linked to emulation, which is in line with prior work showing that people will mirror a variety of different behaviors in others with whom they have high rapport (e.g., Tickle-Degnen and Rosenthal, 1990;Chisholm and Strayer, 1995;Dijksterhuis and Bargh, 2001;Rotenberg et al, 2003;Dijksterhuis, 2005;Chartrand and van Baaren, 2009;Wiltermuth and Heath, 2009;Lubold, 2017).…”

Section: Discussionsupporting

confidence: 83%

A Long-Term Study of Young Children's Rapport, Social Emulation, and Language Learning With a Peer-Like Robot Playmate in Preschool

Kory-Westlund

Breazeal

2019

Front. Robot. AI

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Prior research has demonstrated the importance of children's peers for their learning and development. In particular, peer interaction, especially with more advanced peers, can enhance preschool children's language growth. In this paper, we explore one factor that may modulate children's language learning with a peer-like social robot: rapport. We explore connections between preschool children's learning, rapport, and emulation of the robot's language during a storytelling intervention. We performed a long-term field study in a preschool with 17 children aged 4-6 years. Children played a storytelling game with a social robot for 8 sessions over two months. For some children, the robot matched the level of its stories to the children's language ability, acting as a slightly more advanced peer (Matched condition); for the others, the robot did not match the story level (Unmatched condition). We examined children's use of target vocabulary words and key phrases used by the robot, children's emulation of the robot's stories during their own storytelling, and children's language style matching (LSM-a measure of overlap in function word use and speaking style associated with rapport and relationship) to see whether they mirrored the robot more over time. We found that not only did children emulate the robot more over time, but also, children who emulated more of the robot's phrases during storytelling scored higher on the vocabulary posttest. Children with higher LSM scores were more likely to emulate the robot's content words in their stories. Furthermore, the robot's personalization in the Matched condition led to increases in both children's emulation and their LSM scores. Together, these results suggest first, that interacting with a more advanced peer is beneficial for children, and second, that children's emulation of the robot's language may be related to their rapport and their learning. This is the first study to empirically support that rapport may be a modulating factor in children's peer learning, and furthermore, that a social robot can serve as an effective intervention for language development by leveraging this insight.

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Section: Discussionsupporting

confidence: 83%

A Long-Term Study of Young Children's Rapport, Social Emulation, and Language Learning With a Peer-Like Robot Playmate in Preschool

Kory-Westlund

Breazeal

2019

Front. Robot. AI

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“…Thus, we suspect that the robot's social capabilities (such as nonverbal immediacy) can influence children's learning-as we have seen here and in multiple other studies discussed earlier-but that the influence of social behavior is moderated by other factors, such as the extent to which the robot's sociality is necessary for the learning activity to proceed smoothly (as in the case of conversation and storytelling-based activities), and the extent to which the robot's social behavior helps build rapport. This hypothesis is supported by Lubold and colleagues' recent work with middle school children and adults, in which a social robot with vocal entrainment contributed to increased learning on math tasks, though not increases in self-reported rapport (Lubold et al, 2016(Lubold et al, , 2018Lubold, 2017). Because the vocal entrainment served not only to match pitch and other vocal features, but also made the robot's text-to-speech voice much more expressive, these studies could not disentangle the effects of expressivity from entrainment-however, both expressivity and entrain increase the robot's social capabilities.…”

Section: Relation To Related Workmentioning

confidence: 68%

“…Some recent work has explored increasing prosodic synchrony in a speech-controlled child-robot game in order to promote cooperation and improve enjoyment (Chaspari and Lehman, 2016;Sadoughi et al, 2017). In addition, Lubold and colleagues developed several social voice-adaptive robots that adjust the pitch of the robot's text-to-speech voice to match that of its human interlocutor (Lubold et al, 2015(Lubold et al, , 2016(Lubold et al, , 2018Lubold, 2017). This vocal entrainment contributed to increased learning with undergraduate students as well as middle school students during math tasks, but did not increase self-reported rapport.…”

Section: Speech Entrainmentmentioning

confidence: 99%

“…Some prior work with adults provides evidence in support of this hypothesis (Kidd and Breazeal, 2008;Lubold et al, 2016Lubold et al, , 2018Lubold, 2017); however, there is little work yet exploring a social robot's rapport and relationship with young children. Thus, in this paper, we explored whether enabling a social robot to perform rapport-building behaviors, including speech and behavior entrainment, and giving the robot an appropriate backstory regarding its abilities, could help establish rapport and generate positive interactions with children, which we hypothesized could improve children's learning and engagement.…”

Section: Introductionmentioning

confidence: 99%

“…In positive human-human interpersonal interactions, people frequently mimic each other's behavior—such as posture, affect, speech patterns, gestures, facial expressions, and more—unconsciously, without awareness or intent (Davis, 1982 ; Grammer et al, 1998 ; Philippot et al, 1999 ; Provine, 2001 ; Lakin et al, 2003 ; Semin and Cacioppo, 2008 ; Reitter et al, 2011 ; Borrie and Liss, 2014 ). This mimicry, also called entrainment, is considered a signal of rapport and has been observed in a variety of human relationships (Tickle-Degnen and Rosenthal, 1990 ; Dijksterhuis and Bargh, 2001 ; Rotenberg et al, 2003 ; Dijksterhuis, 2005 ; Chartrand and van Baaren, 2009 ; Wiltermuth and Heath, 2009 ; Lubold, 2017 ), as well as with robots and virtual agents (Breazeal, 2002 ; Bell et al, 2003 ; Suzuki and Katagiri, 2007 ; Levitan et al, 2016 ). While there is less work exploring mimicry and rapport in children, there is some showing that infants and children mimic emotions with humans (Haviland and Lelwica, 1987 ; Chisholm and Strayer, 1995 ; Rotenberg et al, 2003 ) and with robots (Gordon et al, 2016 ).…”

Section: Introductionmentioning

confidence: 99%

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Exploring the Effects of a Social Robot's Speech Entrainment and Backstory on Young Children's Emotion, Rapport, Relationship, and Learning

Kory-Westlund

Breazeal

2019

Front. Robot. AI

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In positive human-human relationships, people frequently mirror or mimic each other's behavior. This mimicry, also called entrainment, is associated with rapport and smoother social interaction. Because rapport in learning scenarios has been shown to lead to improved learning outcomes, we examined whether enabling a social robotic learning companion to perform rapport-building behaviors could improve children's learning and engagement during a storytelling activity. We enabled the social robot to perform two specific rapport and relationship-building behaviors: speech entrainment and self-disclosure (shared personal information in the form of a backstory about the robot's poor speech and hearing abilities). We recruited 86 children aged 3-8 years to interact with the robot in a 2 × 2 between-subjects experimental study testing the effects of robot entrainment Entrainment vs. No entrainment and backstory about abilities Backstory vs. No Backstory. The robot engaged the children one-on-one in conversation, told a story embedded with key vocabulary words, and asked children to retell the story. We measured children's recall of the key words and their emotions during the interaction, examined their story retellings, and asked children questions about their relationship with the robot. We found that the robot's entrainment led children to show more positive emotions and fewer negative emotions. Children who heard the robot's backstory were more likely to accept the robot's poor hearing abilities. Entrainment paired with backstory led children to use more of the key words and match more of the robot's phrases in their story retells. Furthermore, these children were more likely to consider the robot more human-like and were more likely to comply with one of the robot's requests. These results suggest that the robot's speech entrainment and backstory increased children's engagement and enjoyment in the interaction, improved their perception of the relationship, and contributed to children's success at retelling the story.

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Interaction Pace and User Preferences

Goguey

Gutwin

Chen

et al. 2021

Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems

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The overall pace of interaction combines the user's pace and the system's pace, and a pace mismatch could impair user preferences (e.g., animations or timeouts that are too fast or slow for the user). Motivated by studies of speech rate convergence, we conducted an experiment to examine whether user preferences for system pace are correlated with user pace. Subjects frst completed a series of trials to determine their user pace. They then completed a series of hierarchical drag-and-drop trials in which folders automatically expanded when the cursor hovered for longer than a controlled timeout. Results showed that preferences for timeout values correlated with user pace -slow-paced users preferred long timeouts, and fast-paced users preferred short timeouts. Results indicate potential benefts in moving away from fxed or customisable settings for system pace. Instead, systems could improve preferences by automatically adapting their pace to converge towards that of the user. CCS CONCEPTS• Human-centered computing → HCI theory, concepts and models; Empirical studies in HCI.

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Building Rapport through Dynamic Models of Acoustic-Prosodic Entrainment

Cited by 4 publications

References 6 publications

A Long-Term Study of Young Children's Rapport, Social Emulation, and Language Learning With a Peer-Like Robot Playmate in Preschool

A Long-Term Study of Young Children's Rapport, Social Emulation, and Language Learning With a Peer-Like Robot Playmate in Preschool

Exploring the Effects of a Social Robot's Speech Entrainment and Backstory on Young Children's Emotion, Rapport, Relationship, and Learning

Interaction Pace and User Preferences

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